Endoscope processor, endoscope device, and method of generating diagnostic image

ABSTRACT

An endoscope processor includes a processor. The processor detects a first region of a lesion candidate from first image information which is acquired by irradiation with first illumination light; detects a second region of a lesion candidate from second image information acquired by irradiation with second illumination light having a different spectrum from the first illumination light; selects a region for display of the lesion candidate out of the first region and the second region, corresponding to an observation target site of a subject; and generates image information for display, in which the region for display is superimposed on the first image information.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation application of PCT/JP2021/025365filed on Jul. 5, 2021, the entire contents of which are incorporatedherein by this reference.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to an endoscope processor configured todetect a lesion region from image information, an endoscope device, anda method of generating a diagnostic image.

2. Description of the Related Art

Conventionally, endoscopes have been widely used in medical andindustrial fields. For example, when an endoscope is used in the medicalfield, an operator can view an endoscope image of the inside of asubject, which is displayed on a display device, find and discriminate alesion portion, and perform treatment on the lesion portion using atreatment instrument.

In recent years, computer-aided image diagnosis (CAD: computer aideddetection/diagnosis) has been developed which quantitatively analyzes anendoscope image with a computer, and displays a position, discriminationinformation and the like of a lesion candidate on the endoscope image,in order to prevent an operator from overlooking a lesion portion andfacilitate diagnosis. An endoscope device has been proposed thatnotifies the operator of the presence of a lesion portion and a positionwhere the lesion portion exists by highlighting (for example, displayinga marker such as a frame) on the endoscope image when the lesion portionis found by the CAD.

For example, International Publication No. 2019/087971 discloses amedical image processing apparatus and an endoscope device for detectinga lesion region with a first illumination light, discriminating a typeof lesion with a second illumination light, and specifying a degree ofprogress with a third illumination light.

SUMMARY OF THE INVENTION

An endoscope processor according to one aspect of the present inventionincludes a processor, wherein the processor detects a first region of alesion candidate from first image information which is acquired byirradiation with first illumination light; detects a second region of alesion candidate from second image information acquired by irradiationwith second illumination light having a different spectrum from thefirst illumination light; selects a region for display of the lesioncandidate out of the first region and the second region, correspondingto an observation target site of a subject; and generates imageinformation for display, in which the region for display is superimposedon the first image information.

An endoscope device according to one aspect of the present inventionincludes: a light source device that can emit a plurality of types ofillumination light, which include first illumination light and secondillumination light having a different spectrum from the firstillumination light; an endoscope that includes an image pickup apparatusconfigured to acquire first image information on the first illuminationlight radiated from the light source device and acquire second imageinformation on the second illumination light radiated from the lightsource device; an endoscope processor that includes a processorconfigured to detect a first region of a lesion candidate from the firstimage information, detect a second region of a lesion candidate from thesecond image information, select a region for display of the lesioncandidate out of the first region and the second region, correspondingto an observation target site of a subject, and generate imageinformation for display, in which the region for display is superimposedon the first image information; and a monitor configured to display theimage information for display.

A method of generating a diagnostic image according to one aspect of thepresent invention includes: detecting a first region of a lesioncandidate from first image information that is acquired by irradiationwith first illumination light; detecting a second region of a lesioncandidate from second image information acquired by irradiation withsecond illumination light having a different spectrum from the firstillumination light; selecting a region for display of the lesioncandidate out of the first region and the second region, correspondingto an observation target site of a subject; and generating imageinformation for display, in which the region for display is superimposedon the first image information.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a perspective view showing one example of an externalappearance of an endoscope device according to a first embodiment of thepresent invention;

FIG. 2 is a block diagram showing one example of a configuration of theendoscope device according to the above first embodiment;

FIG. 3 is a block diagram showing an example of an electricalconfiguration of an endoscope processor according to the above firstembodiment;

FIG. 4 is a block diagram showing a configuration example of anidentification device according to the above first embodiment;

FIG. 5 is a diagram showing an example of image information in eachidentification device and its monitor in the above first embodiment;

FIG. 6 is a flowchart showing processing of an endoscope processoraccording to the above first embodiment;

FIG. 7 is a block diagram showing a configuration example of anidentification device according to a second embodiment of the presentinvention;

FIG. 8 is a flowchart showing processing of an endoscope processoraccording to the above second embodiment;

FIG. 9 is a block diagram showing a configuration example of anidentification device according to a third embodiment of the presentinvention; and

FIG. 10 is a flowchart showing processing of an endoscope processoraccording to the above third embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Embodiments of the present invention will be described below withreference to the drawings. However, the present invention is not limitedto the embodiments which will be described below. Note that in thedescription of the drawings, the same or corresponding elements areappropriately denoted by the same reference characters.

First Embodiment

FIG. 1 to FIG. 6 show a first embodiment of the present invention, andFIG. 1 is a perspective view showing one example of a configuration ofan endoscope device 1. The endoscope device 1 of the present embodimentincludes: an endoscope 2; a light source device 3; an endoscopeprocessor 4; and a monitor 5.

The endoscope 2 includes: an elongated insertion portion 9 to beinserted into a subject; an operation portion 10 for performing variousoperations related to the endoscope 2; and a universal cable 17 forconnecting the endoscope 2 to the light source device 3 and theendoscope processor 4.

The insertion portion 9 includes a distal end portion 6, a bendingportion 7 and a flexible tube portion 8, in order from a distal endtoward a proximal end side. The distal end portion 6 includes anillumination window through which illumination light is emitted to asubject and an observation window through which return light from thesubject is incident, though the illustration is omitted. The endoscope 2of the present embodiment is configured as an electronic endoscope, andan image pickup apparatus 21 (refer to FIG. 2 ) is provided at thedistal end portion 6. The image pickup apparatus 21 includes an imagepickup optical system and an image pickup device. The image pickupoptical system forms an image of light incident from the observationwindow on the image pickup device, as an optical image of an object(object image). The image pickup device is an image sensor such as CCD(charge coupled device) or CMOS (complementary metal oxidesemiconductor). The image pickup device photoelectrically converts theobject image, and generates and outputs an image pickup signal. Theimage pickup signal is transmitted to the endoscope processor 4 througha signal line.

The bending portion 7 is a bendable portion which is connected to aproximal end side of the distal end portion 6, and changes a directionto which the distal end portion 6 faces, by being bent. By changing thedirection of the distal end portion 6, the observation site of thesubject is changed, or insertability of the endoscope 2 is enhanced.

The flexible tube portion 8 is a portion that is connected to a proximalend side of the bending portion 7 and has flexibility.

A bending wire for bending the bending portion 7 and a treatmentinstrument channel for allowing insertion of a treatment instrument arearranged in the insertion portion 9 and the operation portion 10. In theinsertion portion 9, the operation portion 10 and the universal cable 17of the endoscope 2, the above-described signal line that is connected tothe image pickup device, and a light guide for transmitting illuminationlight are arranged.

In the operation portion 10, there are provided a bending operationportion 14 for bending the bending portion 7 through the bending wire,various switches including a focus switch 15, and the like. In a casewhere the image pickup optical system includes a variable magnificationoptical system, a focus position is changed to a near point or a farpoint by an operation of the focus switch 15, and magnification of asubject image is changed. The bending operation portion 14 includes: aUD bending operation knob 12 for bending the bending portion 7 in avertical direction; and an RL bending operation knob 13 for bending thebending portion 7 in a horizontal direction. The bending portion 7 canalso be bent in an oblique direction, by a combination of bending in thevertical direction and bending in the horizontal direction.

On a distal end side of the operation portion 10, there are provided agrasping portion 11 for an operator so as to grasp the endoscope 2 withhis/her hand, and an insertion port 16 of a treatment instrumentchannel, which serves as an opening on a proximal end side of theabove-described treatment instrument channel.

The universal cable 17 extends from, for example, a side face on aproximal end side of the operation portion 10. A scope connector 17 a isprovided at a proximal end of the universal cable 17. The scopeconnector 17 a removably connects the endoscope 2 to the light sourcedevice 3. By connecting the scope connector 17 a to the light sourcedevice 3, illumination light can be transmitted by the light guide.

A coiled electric cable 18 is extended from a side face of the scopeconnector 17 a. An electric connector 18 a provided at an extension endof the electric cable 18 is removably connected to the endoscopeprocessor 4. By connecting the electric connector 18 a to the endoscopeprocessor 4, the image pickup device is electrically connected to theendoscope processor 4.

The endoscope processor 4 is electrically connected to the monitor 5which is a display device. The endoscope processor 4 processes the imagepickup signal outputted from the image pickup device of the endoscope 2and generates image information for display. The image information fordisplay is outputted from the endoscope processor 4 to the monitor 5,and is displayed on the monitor 5 as a display image including anendoscope image. The monitor 5 includes a speaker 5 a configured tooutput voice.

FIG. 2 is a block diagram illustrating one example of a configuration ofthe endoscope device 1.

As described above, the endoscope 2 includes the image pickup apparatus21. The image pickup apparatus 21 acquires first image information(white light image information which will be described later), bypicking up an image of the subject irradiated with the firstillumination light emitted from the light source device 3, and acquiressecond image information (first special light image information andsecond special light image information which will be described later) bypicking up an image of the subject irradiated with the secondillumination light emitted from the light source device 3.

The light source device 3 can emit a plurality of types of illuminationlight, which include: the first illumination light; and the secondillumination light having a different spectrum from the firstillumination light. The light source device 3 of the present embodimentincludes a white light source 31, a first special light source 32, and asecond special light source 33. The white light source 31 emits whitelight for observation. The first special light source 32 emits firstspecial light having a different spectrum from the spectrum of the whitelight. The second special light source 33 emits second special lighthaving a different spectrum from spectra of the white light and thefirst special light. The white light is the first illumination light,and the first special light and the second special light are the secondillumination light.

More specifically, the light source device 3 includes a plurality oflight sources that emit light of respective colors such as R (red), G(green), B (blue), V (violet) and A (amber), and constitute the whitelight source 31, the first special light source 32, and the secondspecial light source 33 described above, by combining the respectivecolor light sources.

The light source device 3 includes, for example, a light emitting devicesuch as an LED (light emitting diode) or an LD (laser diode). As oneexample, the light source device 3 includes a V-LED that emits violet(V) light having a center wavelength of approximately 405 nm, a B-LEDthat emits blue (B) light having a center wavelength of approximately445 nm, a G-LED that emits green (G) light having a center wavelength ofapproximately 540 nm, and an R-LED that emits red (R) light having acenter wavelength of approximately 630 nm. The light source device 3includes a prism, a mirror, an optical fiber, or an optical filter thatadjusts a wavelength band, a light amount or the like, as necessary.

The light source device 3 of the present embodiment sequentially emits,for example, white light, first special light, and second special light,for each frame. Thereby, the image pickup apparatus 21 repeatedlyacquires white light image information (hereinafter referred to as awhite light image), first special light image information (hereinafterreferred to as a first special light image), and second special lightimage information (hereinafter referred to as a second special lightimage) in this order, and then acquires another white light image afterthe second special light image. However, it is acceptable that eachimage is not limited to being acquired in one frame, but any image isacquired in a plurality of frames. For example, the white light imageand the first special light image are each acquired in one frame, butthe second special light image is acquired in two frames, and the like.

The endoscope processor 4 includes an image processing unit 41, a whitelight identification device 42, a first special light identificationdevice 43, a second special light identification device 44, a lesionregion selection unit 45, a display processing unit 46, a bus 47, and acontrol unit 48.

Note that in FIG. 2 three identification devices are provided which arethe white light identification device 42, the first special lightidentification device 43 and the second special light identificationdevice 44, but two, or four or more identification devices may beprovided. It is also acceptable that a single identification devicehaving a plurality of identification functions is provided and isconfigured to function as any one of the white light identificationdevice 42, the first special light identification device 43, and thesecond special light identification device 44, by switching theidentification functions.

FIG. 3 is a block diagram showing an example of an electricalconfiguration of the endoscope processor 4. In FIG. 2 , a functionalconfiguration of the endoscope processor 4 is shown; but as theelectrical configuration, the endoscope processor 4 includes, forexample, a processor 4 a and a memory 4 b.

The processor 4 a includes, for example, an ASIC (application specificintegrated circuit) including CPU (central processing unit) and thelike, or an FPGA (field programmable gate array). The memory 4 b is astorage medium such as a RAM (random access memory), a flash memory, ora disk storage medium. The memory 4 b includes a non-transitorycomputer-readable storage medium that records a processing program.

The processor 4 a reads and executes the processing program that isstored in the memory 4 b, and thereby performs the functions of therespective units shown in FIG. 2 . However, the present invention is notlimited to the configuration, and the processor 4 a may be configured asa dedicated electronic circuit that performs the function of each unit.

FIG. 4 is a block diagram showing a configuration example of theidentification devices 42, 43 and 44. Any of the white lightidentification device 42, the first special light identification device43 and the second special light identification device 44 includes alesion identification device 4 c that detects a region of a lesioncandidate from image information acquired by irradiation withillumination light. The lesion identification device 4 c includes, forexample, artificial intelligence (AI) that has learned lesion images.

The image processing unit 41 subjects the image information outputtedfrom the image pickup apparatus 21 to various processes such asdemosaicking, noise correction, color correction, contrast correctionand gamma correction; and converts the image information into imagesignals (image information for display) in a format that can beoutputted to the monitor 5.

The white light identification device 42 is a first identificationdevice, and the first special light identification device 43 and thesecond special light identification device 44 are second identificationdevices.

The white light identification device 42 includes an AI that has learnedthe lesion image which has been picked up as a white light image, bymachine learning, deep learning or the like. The white lightidentification device 42 detects a lesion candidate region (first regionof a lesion candidate) from the endoscope image (white light image) thatthe image pickup apparatus 21 has acquired from the white light whichhas been emitted from the white light source 31 and with which thesubject has been irradiated. The white light identification device 42calculates a reliability score of the detected lesion candidate region.The reliability score indicates such a probability (certainty factor)that the lesion candidate region is actually a lesion.

The first special light identification device 43 includes an AI that haslearned the lesion image which has been picked up as a first speciallight image, by machine learning, deep learning or the like. The firstspecial light identification device 43 detects a lesion candidate region(second region of a lesion candidate) from the endoscope image (firstspecial light image) that the image pickup apparatus 21 has acquiredfrom the first special light which has been emitted from the firstspecial light source 32 and with which the subject has been irradiated.The first special light identification device 43 calculates areliability score of the detected lesion candidate region.

The second special light identification device 44 includes an AI thathas learned the lesion image which has been picked up as a secondspecial light image, by machine learning, deep learning or the like. Thesecond special light identification device 44 detects a lesion candidateregion (second region of a lesion candidate) from the endoscope image(second special light image) that the image pickup apparatus 21 hasacquired from the second special light which has been emitted from thesecond special light source 33 and with which the subject has beenirradiated. The second special light identification device 44 calculatesa reliability score of the detected lesion candidate region.

The first special light identification device 43 and the second speciallight identification device 44 can be configured, for example, asidentification devices that detect lesion candidate regions at positions(surface layer, middle layer, and deep layer) the depths from themucosal surface of which are different. The lesion candidate region isdetected based on, for example, an image which emphasizes blood vesselinformation at a target depth. As the special light for emphasizing theblood vessel information, for example, a set (a wavelength set ofnarrowband light optimal for calculating a degree of saturation ofoxygen in the blood vessel at each depth of the surface layer, themiddle layer and the deep layer) is selected, which includes awavelength of narrowband light that sufficiently reaches a target depthand shows a difference in absorption coefficients μa between oxygenatedhemoglobin and reduced hemoglobin, and a wavelength of narrowband lightat an isosbestic point, which does not show the difference. Illuminationlight of such a wavelength set is known as illumination light for NBI(narrow band imaging).

An identification device for a surface layer type lesion identifies amucosal surface, or a surface layer type lesion, the depth from themucosal surface of which is relatively shallow (the depth of which isabout several tens of micrometers from the mucosal surface). The speciallight that emphasizes a surface layer type of blood vessel informationis, for example, the light that includes violet light (405 nm) asreference light, and blue light (445 nm) as measurement light, and inwhich the light amount of the violet light is larger than the lightamount of the blue light. The identification device for the surfacelayer type lesion is an identification device that has been trained withlesion images which have been picked up with the special light thatemphasizes the surface layer type of blood vessel information.

The identification device for a middle layer type lesion identifies themiddle layer type lesion, the depth from the mucosal surface of which isa medium degree (the depth of which is several tens to several hundredsof m). The special light for emphasizing the middle layer type of bloodvessel information includes, for example, the light that includes bluelight (473 nm) as the measurement light, green light as the referencelight, and red light as the reference light, and in which the lightamount of the blue light is larger than the light amount of the greenlight, and the light amount of the green light is larger than the lightamount of the red light. The identification device for the middle layertype lesion is an identification device that has been trained withlesion images which have been picked up with special light thatemphasizes the middle layer type of blood vessel information.

An identification device for a deep layer type lesion identifies a deeplayer type lesion, the depth from the mucosal surface of which is deep(the depth of which is from the muscularis mucosae to the submucosaltissue layer). The identification device for the deep layer type lesionis an identification device or the like which has been trained withlesion images picked up with special light that is the special lightwhich emphasizes the deep layer type of blood vessel information, andincludes, for example, blue light as the reference light, green light asthe reference light, and red light (630 nm) as the measurement light,and in which the light amount of green light is larger than the lightamount of blue light, and the light amount of blue light is larger thanthe light amount of red light.

Note that the identification devices of lesions, the depths from themucosal surface of which are different, have been described as anexample of the second identification device (the first special lightidentification device 43 and the second special light identificationdevice 44), but the second identification devices are not limited to theexample. The second identification device may be, for example, anidentification device that has been trained with lesion images whichhave been picked up with special light (illumination light for RDI (reddichromatic imaging)) that passes through an obstacle in detection of alesion candidate region when picked up with white light, such as residueor bile on a mucous membrane, or blood on the mucous membrane due tobleeding. As the illumination light for RDI, for example, the light isused which includes specific wavelengths of three colors of green, amberand red. Accordingly, the plurality of types of second illuminationlight may include at least one of the illumination light for NBI and theillumination light for RDI.

Note that the present embodiment is described in such a way that thefirst special light identification device 43 is the identificationdevice for the surface layer type lesion, and the second special lightidentification device 44 is the identification device for the middlelayer type lesion, as one example.

The lesion region selection unit 45 selects a region for display of alesion candidate, based on a lesion candidate region that has beendetected by the white light identification device 42, a lesion candidateregion that has been detected by the first special light identificationdevice 43, and a lesion candidate region that has been detected by thesecond special light identification device 44.

As methods for selecting the region for display by the lesion regionselection unit 45, the following methods of (1) to (3) can be used, forexample. Each of the methods (1) to (3) which will be described below isa method of: calculating a plurality of reliability scores including areliability score of a lesion candidate region (first region) of a whitelight image, a reliability score of a lesion candidate region (secondregion) of a first special light image, and a reliability score of alesion candidate region (second region) of a second special light image;and selecting a region for display, based on the plurality ofreliability scores.

In the following, the lesion candidate region detected by the whitelight identification device 42 is referred to as a region 1, the lesioncandidate region detected by the first special light identificationdevice 43 is referred to as a region 2, and the lesion candidate regiondetected by the second special light identification device 44 isreferred to as a region 3. Note that regarding the region 1, there is acase where a lesion candidate is not detected and the region 1 does notexist, and there is a case where one or a plurality of lesion candidatesare detected in one image, and one or a plurality of regions 1 exist.Similarly to the region 1, also in the regions 2 and 3, there is a casewhere there exist zero, one, or a plurality of regions.

(1) The lesion region selection unit 45 firstly extracts a region, thereliability score of which is a predetermined threshold value (specifiedvalue) or larger, among the regions 1 to 3, and when there are aplurality of regions in which the positions overlap among the extractedregions, merges all the regions, and selects the merged region as theregion for display. When there are regions in which the positions do notoverlap among the extracted regions, the lesion region selection unit 45selects the regions as the regions for display as the regions are.

(2) The lesion region selection unit 45 firstly extracts a region, thereliability score of which is a predetermined threshold value (specifiedvalue) or larger, among the regions 1 to 3, and when there are aplurality of regions in which the positions overlap among the extractedregions, selects a region, the reliability score of which is highest, asthe region for display. When there are regions in which the positions donot overlap among the extracted regions, the lesion region selectionunit 45 selects the regions as the regions for display as the regionsare.

(3) The lesion region selection unit 45 assigns weights to thereliability scores corresponding to the observation target site (organto be subjected to endoscopic examination) of the subject, applies themethod (2) based on the weighted reliability score, and selects theregion for display.

The method (3) will be further described below. In the following, thereliability score of the region 1 is referred to as a score 1, thereliability score of the region 2 is referred to as a score 2, and thereliability score of the region 3 is referred to as a score 3, asappropriate. A weight coefficient by which the score 1 is multiplied isreferred to as a weight coefficient 1, a weight coefficient by which thescore 2 is multiplied is referred to as a weight coefficient 2, and aweight coefficient by which the score 3 is multiplied is referred to asa weight coefficient 3.

As for organs such as the esophagus and the large intestine, adiagnostic method is being established which uses an image picked upwith the special light that emphasizes the surface layer type of bloodvessel information. Then, in a case where the organ is the esophagus orthe large intestine, the lesion region selection unit 45 sets the weightcoefficient 2 so as to be larger than the weight coefficient 1 and theweight coefficient 3, applies the method (2), and selects the region fordisplay. At the time, if the weight coefficient 1 and the weightcoefficient 3 are set to 0, only the region 2 results in being selectedas an object, which has been detected by the first special lightidentification device 43 that is an identification device of the surfacelayer type lesion, and the operation is the same as an operation ofselecting the first special light identification device 43 as theidentification device.

In a case where the organ is the stomach and the lesion is a scirrhousgastric cancer, a diagnostic method is being established which uses animage picked up with the special light that emphasizes a middle layertype of blood vessel information. Then, in a case where the organ is thestomach, the lesion region selection unit 45 sets the weight coefficient3 so as to be larger than the weight coefficient 1 and the weightcoefficient 2, applies the method (2), and selects the region fordisplay. At the time, if the weight coefficient 1 and the weightcoefficient 2 are set to 0, only the region 3 results in being selectedas an object, which has been detected by the second special lightidentification device 44 that is an identification device of the middlelayer type lesion, and the operation is the same as an operation ofselecting the second special light identification device 44 as theidentification device.

Accordingly, it differs depending on the organ which one is selected asthe region for display, among the lesion candidate region of the whitelight image (first region), the lesion candidate region of the firstspecial light image (second region), and the lesion candidate region ofthe second special light image (second region).

The assignment of the weight corresponding to the organ may be switchedaccording to a user instruction (in other words, manually); may beautomatically switched by the control unit 48 which determines theassignment of the weight based on the feature of the endoscope image;may be automatically switched by the control unit 48 which detects aninsertion length of the insertion portion 9 of the endoscope 2 anddetermines the assignment of the weight based on the detection result;or may be automatically switched by the control unit 48 which determinesthe assignment of the weight based on a detection result of a positiondetection sensor which is incorporated in the distal end portion 6 ofthe endoscope 2.

The white light image is transmitted from the image processing unit 41to the display processing unit 46, through the white lightidentification device 42 and the lesion region selection unit 45.Furthermore, the region for display selected by the lesion regionselection unit 45 is transmitted to the display processing unit 46.

The bus 47 is a transmission channel through which each unit in theendoscope processor 4 transmits and receives commands and information.

The control unit 48 is connected to the image processing unit 41, thewhite light identification device 42, the first special lightidentification device 43, the second special light identification device44, the lesion region selection unit 45 and the display processing unit46, through the bus 47, and controls the units and the devices.

The control unit 48 includes a motion detection unit 48 a. The motiondetection unit 48 a detects the motion of the white light image, thefirst special light image and the second special light image. Thecontrol unit 48 may detect the motion, for example, by image analysis,or may detect the motion based on a detection result of an accelerationsensor or the above-described position detection sensor, which has beenincorporated in the distal end portion 6 of the endoscope 2.

The motion of the image occurs due to the movement of the image pickupapparatus 21 relative to the subject, which is provided at the distalend portion 6 of the endoscope 2. Types of the motion of the imageinclude: for example, movement in the vertical direction and thehorizontal direction on the screen; rotation movement of the imagepickup apparatus 21 relative to the subject; and movement ofexpansion/contraction of an image due to approach/separation of thedistal end portion 6 to/from the subject (or due to variablemagnification in a case where the image pickup apparatus 21 includes avariable magnification optical system). The control unit 48 transmitsmotion information of the image detected by the motion detection unit 48a, to the lesion region selection unit 45 and the display processingunit 46.

Based on the motion information of the images transmitted from thecontrol unit 48, the lesion region selection unit 45 aligns the imageswith each other (corrects positional displacement), (accordingly, alignsthe lesion candidate regions in the images with each other), and thenselects a region for display from among regions 1 to 3.

The display processing unit 46 aligns the region for display with thewhite light image based on the motion information of the imagetransmitted from the control unit 48. However, it is also acceptablethat the lesion region selection unit 45 aligns the region for displaywith the white light image. The display processing unit 46 generatesimage information for display by superimposing the region for display onthe white light image, and outputs the generated image information fordisplay to the monitor 5. Note that the region for display to besuperimposed on the white light image may be, for example, a contourline of a merged region, or may be a marker (for example, a rectangularframe) which indicates a range of the merged region.

The monitor 5 displays a display image on a monitor screen, according tothe image information for display, which has been inputted from thedisplay processing unit 46.

FIG. 5 is a diagram showing an example of image information in each ofidentification devices 42, 43 and 44, and the monitor 5.

The white light identification device 42 detects a lesion candidateregion 51 a from a white light image 51.

The first special light identification device 43 detects a lesioncandidate region 52 a from a first special light image 52.

The second special light identification device 44 detects a lesioncandidate region 53 a from a second special light image 53.

The monitor 5 displays on the monitor screen a display image 50 on whicha region for display 50 a is superimposed. Here, the region for display50 a is, for example, a region obtained by merging of the lesioncandidate region 51 a, the lesion candidate region 52 a and the lesioncandidate region 53 a. Note that the display of a discrimination result50 b and a degree of progress 50 c shown in FIG. 5 will be described ina later embodiment.

FIG. 6 is a flowchart showing the processing of the endoscope processor4. FIG. 6 shows an example in which the endoscope processor 4sequentially acquires the white light image, the first special lightimage and the second special light image, in every three frames.

For example, at an n-th frame (n is an integer), the light source device3 emits white light, and the image pickup apparatus 21 acquires a whitelight image. The acquired white light image is inputted to the endoscopeprocessor 4 (step S1). The inputted white light image is processed bythe image processing unit 41, and then is sent to the white lightidentification device 42 and the display processing unit 46.

The white light identification device 42 detects a lesion candidateregion from the white light image by the lesion identification device 4c in the white light identification device 42, and also calculates areliability score for each detected lesion candidate region (step S2).

In a case where the lesion candidate region has been detected, thecontrol unit 48 determines whether or not the reliability scorecalculated by the white light identification device 42 is a specifiedvalue (threshold value) or larger for each lesion candidate region (stepS3). Note that in a case where the lesion candidate region is notdetected, the control unit 48 skips the processing of step S3 andproceeds to step S4.

In a case where the lesion candidate region is not detected or it isdetermined that the reliability scores of all the lesion candidateregions are smaller than the specified value, the control unit 48determines that there is no lesion (step S4), and does not cause thewhite light identification device 42 to transmit the lesion candidateregion to the lesion region selection unit 45 even if there is a lesioncandidate region.

In a case where it is determined that there is a lesion candidateregion, the reliability score of which is the specified value or larger,the control unit 48 causes the white light identification device 42 totransmit the lesion candidate region to the lesion region selection unit45.

In a subsequent (n+1)-th frame, the light source device 3 emits thefirst special light which emphasizes a surface layer blood vessel, andthe image pickup apparatus 21 acquires the first special light image.The acquired first special light image is inputted to the endoscopeprocessor 4 (step S5). The inputted first special light image isprocessed by the image processing unit 41, and then is sent to the firstspecial light identification device 43.

The first special light identification device 43 detects a lesioncandidate region from the first special light image by the lesionidentification device 4 c in the first special light identificationdevice 43, and also calculates a reliability score for each detectedlesion candidate region (step S6).

In a case where the lesion candidate region has been detected, thecontrol unit 48 determines whether or not the reliability scorecalculated by the first special light identification device 43 is aspecified value (threshold value) or larger for each lesion candidateregion (step S7). Note that in a case where the lesion candidate regionis not detected, the control unit 48 skips the processing of step S7 andproceeds to step S8.

In a case where the lesion candidate region is not detected or it isdetermined that the reliability scores of all the lesion candidateregions are smaller than the specified value, the control unit 48determines that there is no lesion (step S8), and does not cause thefirst special light identification device 43 to transmit the lesioncandidate region to the lesion region selection unit 45 even if there isa lesion candidate region.

In a case where it is determined that there is a lesion candidateregion, the reliability score of which is the specified value or larger,the control unit 48 causes the first special light identification device43 to transmit the lesion candidate region to the lesion regionselection unit 45.

In the subsequent (n+2)-th frame, the light source device 3 emits thesecond special light which emphasizes a middle layer blood vessel, andthe image pickup apparatus 21 acquires the second special light image.The acquired second special light image is inputted to the endoscopeprocessor 4 (step S9). The inputted second special light image isprocessed by the image processing unit 41, and then is sent to thesecond special light identification device 44.

The second special light identification device 44 detects a lesioncandidate region from the second special light image by the lesionidentification device 4 c in the second special light identificationdevice 44, and also calculates a reliability score for each detectedlesion candidate region (step S10).

In a case where the lesion candidate region has been detected, thecontrol unit 48 determines whether or not the reliability scorecalculated by the second special light identification device 44 is aspecified value (threshold value) or larger for each lesion candidateregion (step S11). Note that in a case where the lesion candidate regionis not detected, the control unit 48 skips the processing of step S11and proceeds to step S12.

In a case where the lesion candidate region is not detected or it isdetermined that the reliability scores of all the lesion candidateregions are smaller than the specified value, the control unit 48determines that there is no lesion (step S12), and does not cause thesecond special light identification device 44 to transmit the lesioncandidate region to the lesion region selection unit 45 even if there isa lesion candidate region.

In a case where it is determined that there is a lesion candidateregion, the reliability score of which is the specified value or larger,the control unit 48 causes the second special light identificationdevice 44 to transmit the lesion candidate region to the lesion regionselection unit 45.

In a case where it is determined in step S3 that the reliability scoreis the specified value or larger, in a case where it is determined instep S7 that the reliability score is the specified value or larger, orin a case where it is determined in step S11 that the reliability scoreis the specified value or larger, the lesion region selection unit 45selects a region for display from the lesion candidate regions obtainedbased on the images of the n-th to (n+2)-th frames (step S13). Here, thelesion region selection unit 45, for example, aligns all the inputtedlesion candidate regions as described above, then merges the alignedregions, and sets the aligned regions as the region for display. Inother words, all of the lesion candidate regions processed by the lesionregion selection unit 45 are regions, the reliability scores of whichare the specified value or larger.

Subsequently, the display processing unit 46 synthesizes an image byaligning the regions for display and superimposing the aligned regionson the white light image (first image information), and generates imageinformation for display (step S14). The generated image information fordisplay is outputted from the endoscope processor 4 to the monitor 5,and the display image is displayed on the monitor screen of the monitor5.

After the (n+2)-th frame has been processed, the subsequent (n+3)-th,(n+4)-th and (n+5)-th frames are processed in the same way as theabove-described n-th, (n+1)-th and (n+2)-th frames, and the subsequentframes are processed in the same way.

Note that when image information for display is generated once everythree frames and the display image is displayed, a frame rate decreases.Then, in order that the frame rate does not decease, it is alsoacceptable to sequentially display a display image based on the imagesof the n-th to (n+2)-th frames, next display a display image based onimages of (n+1)-th to (n+3)-th frames, and further display a displayimage based on the images of (n+2)-th to (n+4)-th frames and so on.

According to the first embodiment as in the above, the endoscope deviceis configured to detect a plurality of lesion candidate regions from aplurality of pieces of image information acquired by irradiation with aplurality of types of illumination light having different spectraincluding white light, select a region for display from the plurality oflesion candidate regions, and generate image information for display, inwhich the selected region for display is superimposed on the white lightimage; and can realize a function of detecting a lesion that may beoverlooked with white light. The operator can visually recognize, in thewhite light image, the details of the subject, which are dark anddifficult to see in a special light image.

Furthermore, the endoscope device uses a plurality of types of secondillumination light, that is, the first special light and the secondspecial light, and can detect, for example, lesions, the depths from themucosal surface of which are different, from the respective images.

At the time, when illumination light for NBI (narrow band imaging) isused as the second illumination light, the blood vessel can beemphasized. When illumination light for RDI (red dichromatic imaging) isused as the second illumination light, it is possible to detect a lesionwhile penetrating an obstacle such as a residue, bile or blood.

The endoscope device also selects the region for display of the lesioncandidate based on the reliability score, and thereby can enhancedetection accuracy for the lesion. At the time, the endoscope deviceselects the region for display from a region in which the reliabilityscore is higher than the threshold value, and thereby, the operator canconcentrate on the observation of the region which is highly likely tocontain the lesion.

The endoscope device changes which illumination light-related imageinformation is used for selecting the lesion candidate region that hasbeen detected as the region for display, corresponding to the organ thatis the observation target site of the subject, and thereby can performaccurate computer-aided image diagnosis (CAD: computer aideddetection/diagnosis) corresponding to lesions for which a diagnosismethod has been established.

The endoscope device firstly aligns the lesion candidate regionsdetected from the plurality of pieces of image information according tothe results of the motion detection, then selects a region for display,and generates the image information for display; and thereby can performmarker display or the like at an appropriate position on the white lightimage, even in a case where there is movement among a plurality ofimages.

Thus, the endoscope device selects a region for display of a lesioncandidate by comprehensive determination based on a plurality of typesof images including a white light image and a special light image, andperforms computer-aided image diagnosis in which the region for displayis displayed on a white light image with a marker or the like; andthereby overlooking of the lesion is reduced, the lesion is easilyfound, and the scale of the lesion is accurately and easily grasped.Thereby, it becomes easier for the operator to view the display imageand make a diagnosis.

Second Embodiment

FIG. 7 and FIG. 8 show a second embodiment of the present invention, andFIG. 7 is a block diagram showing a configuration example of theidentification devices 42, 43 and 44. In the second embodiment, portionssimilar to the portions of the above described first embodiment aredenoted by the same reference characters; and description of theportions will be omitted as appropriate, and only different points willbe mainly described.

In the present embodiment, in addition to the display of the lesioncandidate region in the first embodiment described above, adiscrimination result for the lesion candidate region is displayed.

As shown in FIG. 7 , each of the white light identification device 42,the first special light identification device 43, and the second speciallight identification device 44 of the present embodiment includes adiscrimination identification device 4 d in addition to the lesionidentification device 4 c.

The discrimination identification device 4 d includes, for example, anAI that has learned lesion images. The discrimination identificationdevice 4 d discriminates the type of each lesion with respect to one ormore lesion candidate regions that have been detected by the lesionidentification device 4 c, and calculates a reliability score of thetype of lesion, which has been discriminated.

The discrimination identification device 4 d identifies that the lesioncandidate region is, for example, a “polyp”, and calculates that thereliability score of being a “polyp” is, for example, “60%”.

However, the discrimination identification device 4 d does notnecessarily output one discrimination result, and may outputdiscrimination results for a plurality of types of lesions, such as “thereliability score of being a polyp is 60%,” “the reliability score ofbeing ulcerative colitis is 10%”, and “the reliability score of beingCrohn's disease is less than 1%”.

Note that in FIG. 7 , the lesion identification device 4 c and thediscrimination identification device 4 d are described as separateblocks, but one AI may be configured to function as both blocks.

FIG. 8 is a flowchart showing the processing of the endoscope processor4. In FIG. 8 , portions different from the portions in FIG. 6 will bedescribed below.

The white light identification device 42 subjects the white light imagewhich has been acquired in the n-th frame to the processing of step S2,and also the discrimination identification device 4 d in the white lightidentification device 42 discriminates the lesion candidate region whichhas been detected by the lesion identification device 4 c in the whitelight identification device 42. The discrimination identification device4 d calculates a discrimination result of the lesion candidate region,and a reliability score for the discrimination result (step S21). Notethat in a case where the lesion candidate region is not detected by thelesion identification device 4 c, the discrimination identificationdevice 4 d skips the processing of step S21.

The first special light identification device 43 subjects the firstspecial light image acquired in the (n+1)-th frame to the processing ofstep S6, and the discrimination identification device 4 d in the firstspecial light identification device 43 discriminates the lesioncandidate region detected by the lesion identification device 4 c in thefirst special light identification device 43. The discriminationidentification device 4 d calculates a discrimination result of thelesion candidate region, and a reliability score for the discriminationresult (step S22). Note that in a case where the lesion candidate regionis not detected by the lesion identification device 4 c, thediscrimination identification device 4 d skips the processing of stepS22.

The second special light identification device 44 subjects the secondspecial light image acquired in the (n+2)-th frame to the processing ofstep S10, and the discrimination identification device 4 d in the secondspecial light identification device 44 discriminates the lesioncandidate region detected by the lesion identification device 4 c in thesecond special light identification device 44. The discriminationidentification device 4 d calculates a discrimination result of thelesion candidate region, and a reliability score for the discriminationresult (step S23). Note that in a case where the lesion candidate regionis not detected by the lesion identification device 4 c, thediscrimination identification device 4 d skips the processing of stepS23.

The lesion region selection unit 45 performs the processing of step S13;also compares the reliability score for the discrimination resultobtained in step S21, the reliability score for the discriminationresult obtained in step S22, and the reliability score for thediscrimination result obtained in step S23; determines whichdiscrimination result is to be displayed; and outputs the determineddiscrimination result to the display processing unit 46 (step S24).

Here, the lesion region selection unit 45 may determine, for example, adiscrimination result in which the reliability score is highest, as thediscrimination result to be displayed. The lesion region selection unit45 may also determine several (that is, a plurality of) discriminationresults in descending order of the reliability score as thediscrimination results to be displayed, and may display the reliabilityscores, side by side with the discrimination results to be displayed.

The display processing unit 46 synthesizes an image by aligning theregions for display and superimposing the aligned regions on the whitelight image (first image information), further synthesizes an imagewhich includes the discrimination result in the vicinity of the whitelight image, and generates image information for display (step S14A).The generated image information for display is outputted from theendoscope processor 4 to the monitor 5, and the display image isdisplayed on the monitor screen of the monitor 5. Thereby, thediscrimination result 50 b as shown in FIG. 5 is displayed.

According to the second embodiment, the endoscope device showssubstantially the same effect as the effect of the first embodimentdescribed above, and can reduce the variation of the diagnosis due tothe subjectivity of the operator with respect to the type of lesion,because of being configured to discriminate the type of lesion andgenerate image information for display including the discriminationresult.

Third Embodiment

FIG. 9 and FIG. 10 show a third embodiment of the present invention, andFIG. 9 is a block diagram showing a configuration example of theidentification devices 42, 43 and 44. In the third embodiment, portionssimilar to the portions of the above described first and secondembodiments are denoted by the same reference characters; anddescription of the portions will be omitted as appropriate, and onlydifferent points will be mainly described.

The present embodiment is configured to display a degree of progress ofthe lesion, in addition to the display of the lesion candidate regionand the discrimination result in the second embodiment described above.

As shown in FIG. 9 , each of the white light identification device 42,the first special light identification device 43 and the second speciallight identification device 44 of the present embodiment includes aprogress degree identification device 4 e in addition to the lesionidentification device 4 c and the discrimination identification device 4d.

The progress degree identification device 4 e includes, for example, anAI that has learned lesion images. The progress degree identificationdevice 4 e identifies the degree of progress of the lesion that has beendiscriminated by the discrimination identification device 4 d withrespect to the lesion candidate region, and calculates a reliabilityscore of the degree of progress.

Note that in FIG. 9 , the lesion identification device 4 c, thediscrimination identification device 4 d and the progress degreeidentification device 4 e are described as separate blocks, but one AImay be configured to function as three blocks.

In the endoscopic finding classification of a polyp (including cancer),for example, there are NICE (the narrow-band imaging internationalcolorectal endoscopic) classification, JNET (the Japan NBI (narrow bandimaging) expert team) classification, and the like.

In a case where the progress degree identification device 4 e identifiesthe degree of progress of a polyp according to the NICE classification,for example, the progress degree identification device 4 e identifiesthe degree of progress as any one of “NICE Type1”, “NICE Type2” and“NICE Type3”. “NICE Type1” indicates hyperplastic lesions, “NICE Type2”indicates adenoma to intramucosal cancer (so-called M cancer), and “NICEType3” indicates submucosal invasive cancer (so-called SM cancer).

In endoscopic finding classification of ulcerative colitis, there areMayo classification, Matts classification, UCEIS (ulcerative colitisendoscopic index of severity) classification and the like.

In a case where the progress degree identification device 4 e identifiesthe degree of progress of ulcerative colitis according to the Mayoclassification, for example, the progress degree identification device 4e identifies the degree of progress as any one of four grades of Mayo0(grade 0), Mayo1 (grade 1), Mayo2 (grade 2) and Mayo3 (grade 3). Mayo0is a grade that indicates a normal or inactive state (includingremission). Mayo1 is a grade that indicates a mild symptom, and isgenerally a state in which redness, an unclear blood vessel image, or amild hemorrhagic symptom is observed. Mayo2 is a grade that indicates amoderate symptom, and is generally a state in which marked redness,disappearance of a blood vessel image, a hemorrhagic symptom, adhesionof purulent secretion, a coarse mucous membrane, erosion, partialulceration or the like is observed. Mayo3 is a grade that indicates asevere symptom (active stage), and is generally a state in whichapparent spontaneous hemorrhage, edema, ulcer (including extensiveulceration) or the like is observed. The progress degree identificationdevice 4 e may also identify dysplasia associated with ulcerativecolitis.

In the endoscopic finding classification of Crohn's disease, there areSESCD (simple endoscopic score for Crohn's disease) and the like. In acase where the progress degree identification device 4 e identifies thedegree of progress of Crohn's disease according to SESCD, the progressdegree identification device 4 e identifies the degree of progress asany one of “SESCD 0”, “SESCD 1”, “SESCD 2” and “SESCD 3”.

Note that in a case where the lesion region selection unit 45 determinesa plurality of discrimination results as discrimination results to bedisplayed in descending order of reliability score, the progress degreeidentification device 4 e also identifies the degree of progress foreach of the plurality of discrimination results.

FIG. 10 is a flowchart showing the processing of the endoscope processor4. In FIG. 10 , portions different from the portions in FIG. 8 will bedescribed below.

The white light identification device 42 subjects the white light imagewhich has been acquired in the n-th frame to the processes of step S2and step S21, and also identifies the degree of progress for the lesionthat has been discriminated by the discrimination identification device4 d in the white light identification device 42, with the progressdegree identification device 4 e in the white light identificationdevice 42. The progress degree identification device 4 e calculates anidentification result of the degree of progress, and a reliability scorefor the identified degree of progress (step S31). Note that in a casewhere the lesion candidate region is not detected by the lesionidentification device 4 c, the discrimination identification device 4 dskips the processing of step S31.

The first special light identification device 43 subjects the firstspecial light image which has been acquired in the (n+1)-th frame to theprocesses of step S6 and step S22, and also identifies the degree ofprogress for the lesion that has been discriminated by thediscrimination identification device 4 d in the first special lightidentification device 43, with the progress degree identification device4 e in the first special light identification device 43. The progressdegree identification device 4 e calculates an identification result ofthe degree of progress, and a reliability score for the identifieddegree of progress (step S32). Note that in a case where the lesioncandidate region is not detected by the lesion identification device 4c, the discrimination identification device 4 d skips the processing ofstep S32.

The second special light identification device 44 subjects the secondspecial light image which has been acquired in the (n+2)-th frame to theprocesses of step S10 and step S23, and also identifies the degree ofprogress for the lesion that has been discriminated by thediscrimination identification device 4 d in the second special lightidentification device 44, with the progress degree identification device4 e in the second special light identification device 44. The progressdegree identification device 4 e calculates an identification result ofthe degree of progress, and a reliability score for the identifieddegree of progress (step S33). Note that in a case where the lesioncandidate region is not detected by the lesion identification device 4c, the discrimination identification device 4 d skips the processing ofstep S33.

The lesion region selection unit 45 performs the processes of step S13and step S24, determines the degree of progress corresponding to thediscrimination result that has been determined to be displayed in stepS24, on the basis of the reliability score, and outputs the determineddegree of progress to the display processing unit 46 (step S34).

For example, in a case where the discrimination result to be displayedis ulcerative colitis, suppose that such a reliability score is 30% thatthe degree of progress is Mayo0 (grade 0), such a reliability score is60% that the degree of progress is Mayo1 (grade 1), such a reliabilityscore is 10% that the degree of progress is Mayo2 (grade 2), and such areliability score is smaller than 1% that the degree of progress isMayo3 (grade 3). At the time, the lesion region selection unit 45determines, for example, “Mayo1”, the reliability score of which ishighest, as the degree of progress, and outputs the degree of progressto the display processing unit 46.

The display processing unit 46 synthesizes an image by aligning theregions for display and superimposing the aligned regions on the whitelight image (first image information), further synthesizes an imagewhich includes the discrimination result and the degree of progress inthe vicinity of the white light image, and generates image informationfor display (step S14B). The generated image information for display isoutputted from the endoscope processor 4 to the monitor 5, and thedisplay image is displayed on the monitor screen of the monitor 5.Thereby, the discrimination result 50 b and the degree of progress 50 cas shown in FIG. 5 are displayed.

According to the third embodiment, the endoscope device showssubstantially the same effects as the effects of the first and secondembodiments described above, and can reduce the variation of thediagnosis due to the subjectivity of the operator with respect to thedegree of progress of a lesion, because of being configured to identifythe degree of progress of the lesion and generate image information fordisplay including the degree of progress.

Note that in the above description, the case has been mainly describedwhere the present invention is the endoscope processor and the endoscopedevice including the endoscope processor, but the present invention isnot limited to the case. The present invention may be a method ofgenerating a diagnostic image, which performs processing similar to theprocessing of the endoscope processor. The present invention may also bea computer program for causing a computer to perform the same processingas the endoscope processor performs; a non-transitory computer-readablerecording medium that records the computer program; or the like.

Furthermore, the present invention is not limited to the above-describedembodiments as the embodiments are, and can be embodied by suchmodification of components within such a range as not to depart from thegist of the invention, in an implementation stage. Various aspects ofthe invention can be formed by appropriate combinations of a pluralityof components that are disclosed in the above embodiments. For example,some components may be deleted from all the components shown in theembodiments. Furthermore, components in different embodiments may beappropriately combined. Thus, it goes without saying that variousmodifications and applications can be made without departing from thegist of the invention.

What is claimed is:
 1. An endoscope processor comprising a processor,wherein the processor detects a first region of a lesion candidate fromfirst image information which is acquired by irradiation with firstillumination light; detects a second region of a lesion candidate fromsecond image information acquired by irradiation with secondillumination light having a different spectrum from the firstillumination light; selects a region for display of the lesion candidateout of the first region and the second region, corresponding to anobservation target site of a subject; and generates image informationfor display, in which the region for display is superimposed on thefirst image information.
 2. The endoscope processor according to claim1, wherein the first illumination light is white light.
 3. The endoscopeprocessor according to claim 1, wherein the processor is configured todetect a plurality of second regions from a plurality of pieces ofsecond image information acquired by irradiation with a plurality oftypes of second illumination light having different spectra from eachother; and select the region for display from among the first region andthe plurality of second regions.
 4. The endoscope processor according toclaim 3, wherein the plurality of types of second illumination lightinclude at least one of illumination light for NBI (narrow band imaging)and illumination light for RDI (red dichromatic imaging).
 5. Theendoscope processor according to claim 1, wherein the processor isconfigured to calculate a plurality of reliability scores including areliability score of the first region and a reliability score of thesecond region; and select the region for display, based on the pluralityof reliability scores.
 6. The endoscope processor according to claim 5,wherein the processor is configured to select the region for display outof the first region and the second region in which the reliability scoreis higher than a threshold value.
 7. The endoscope processor accordingto claim 6, wherein the processor is configured to select a region inwhich the reliability score is highest in the first region and thesecond region as the region for display, in a case where a position ofthe first region and a position of the second region overlap each other.8. The endoscope processor according to claim 6, wherein the processoris configured to select a region in which the first region and thesecond region are merged as the region for display, in a case where aposition of the first region and a position of the second region overlapeach other.
 9. The endoscope processor according to claim 3, wherein theprocessor is configured to calculate a plurality of reliability scoresincluding a reliability score of the first region and a reliabilityscore of each of the plurality of second regions, and select the regionfor display, based on the plurality of reliability scores.
 10. Theendoscope processor according to claim 9, wherein the processor isconfigured to multiply the plurality of reliability scores by aplurality of weight coefficients corresponding to the observation targetsite of the subject, respectively, and select the region for display,based on the plurality of reliability scores that are multiplied by theplurality of weight coefficients, respectively.
 11. The endoscopeprocessor according to claim 10, wherein the observation target site isan organ, and the processor sets the plurality of weight coefficientscorresponding to a type of the organ.
 12. The endoscope processoraccording to claim 10, wherein the processor automatically switches theplurality of weight coefficients, corresponding to the observationtarget site.
 13. The endoscope processor according to claim 1, whereinthe processor is configured to detect motions of the first imageinformation and the second image information, and align the first regionand the second region according to a result of the detected motions,then select the region for display, and generate the image informationfor display.
 14. The endoscope processor according to claim 1, whereinthe processor is configured to discriminate a type of lesion in theregion for display, and generate the image information for displayincluding a discrimination result.
 15. The endoscope processor accordingto claim 14, wherein the processor is configured to identify a degree ofprogress of the lesion obtained as the discrimination result, andgenerate the image information for display including the degree ofprogress.
 16. An endoscope device comprising: a light source device thatcan emit a plurality of types of illumination light, which include firstillumination light and second illumination light having a differentspectrum from the first illumination light; an endoscope that includesan image pickup apparatus configured to acquire first image informationon the first illumination light radiated from the light source deviceand acquire second image information on the second illumination lightradiated from the light source device; an endoscope processor thatincludes a processor configured to detect a first region of a lesioncandidate from the first image information, detect a second region of alesion candidate from the second image information, select a region fordisplay of the lesion candidate out of the first region and the secondregion, corresponding to an observation target site of a subject, andgenerate image information for display, in which the region for displayis superimposed on the first image information; and a monitor configuredto display the image information for display.
 17. A method of generatinga diagnostic image comprising: detecting a first region of a lesioncandidate from first image information that is acquired by irradiationwith first illumination light; detecting a second region of a lesioncandidate from second image information acquired by irradiation withsecond illumination light having a different spectrum from the firstillumination light; selecting a region for display of the lesioncandidate out of the first region and the second region, correspondingto an observation target site of a subject; and generating imageinformation for display, in which the region for display is superimposedon the first image information.
 18. The method of generating adiagnostic image according to claim 17, further comprising: detecting aplurality of second regions from a plurality of pieces of second imageinformation acquired by irradiation with a plurality of types of secondillumination light having different spectra from each other; calculatinga plurality of reliability scores including a reliability score of thefirst region and a reliability score of each of the plurality of secondregions; multiplying the plurality of reliability scores by a pluralityof weight coefficients corresponding to the observation target site ofthe subject, respectively; and selecting the region for display fromamong the first region and the plurality of second regions, based on theplurality of reliability scores that are multiplied by the plurality ofweight coefficients, respectively.
 19. The method of generating adiagnostic image according to claim 18, wherein the observation targetsite is an organ, and the plurality of weight coefficients are set,corresponding to a type of the organ.
 20. The method of generating adiagnostic image according to claim 18, further comprising:automatically switching the plurality of weight coefficients,corresponding to the observation target site.